Poster — Wed Eve—20: Evolving Standards of Education and Training in Medical Physics in Six Regions of the World
Bibliographic record
Abstract
Significant resources are allocated for applying Medical Physics to health care. State‐ of‐ the‐ art technological developments have made this discipline valuable in early diagnosis and treatment of many diseases, particularly cancer. There is a dire need to harmonize the standards of practice in order to cope with modern technology. This should be done by optimising education and training (E & T) in Medical Physics across various countries. With experiences gained from the successes and failures in this field, standards of practice have evolved in the developed as well as the developing countries, but at different rates. Considerations of regional economic conditions and priorities have led to increased gaps in these standards of practice. This discussion focuses on the status of E&T in Africa, South East Asia, Australia, Europe, Middle East, and North America. The evolution of standards in different regions is examined with due consideration to regionally‐influenced factors. Suggestions have been made to optimise rather than equalise the standards.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.045 | 0.010 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".